动态加权和测量方差时变的多传感器融合算法

Algorithm of Multi-sensor Fusion Based on Dynamic weight and Time-varying Measurement Variance

在基于卡尔曼滤波及其一些改进算法中,由于测量方差预先设定,从而导致滤波发散和信息资源的浪费,为此提出了一种动态加权下测量方差时变的多传感器融合算法。该算法依据各传感器当前时刻的滤波精度合理地分配权值,同时测量方差的时变特性使得每次测量信息得到充分的利用。仿真结果表明该算法显著地提高了对机动目标的跟踪效果并具有实时性的优点。

In the algorithm based on Kalman filter and its extension, the presupposition of the measurement variance leads to filter divergence and waste of information, Hence , a new algorithm of multi - sensor fusion is presented based on time - varying of measurement variance and dynamic weight. The algorithm reasonably distributes weight value according to the filter accuracy renewed of each sensor, meanwhile, the specific property of time - varying in measurement variance makes innovation obtained each time sufficiently utilized. The simulation shows that this algorithm can obviously improve the efficiency of maneuvering target tracking on the base of possessing real - time merit.